DocumentCode
394122
Title
Evolving connectionist systems for adaptive learning and knowledge discovery: methods, tools, applications
Author
Kasabov, Nikola
Author_Institution
Knowledge Eng. & Discovery Res. Inst., Auckland Univ. of Technol., New Zealand
Volume
2
fYear
2002
fDate
18-22 Nov. 2002
Firstpage
590
Abstract
The paper describes what evolving processes are and presents a computational model called evolving connectionist systems (ECOS). The model is based on principles from both brain organization and genetics. The applicability of the model for dynamic modeling and knowledge discovery in the areas of brain study, bioinformatics, speech and language learning, adaptive control and adaptive decision support is discussed.
Keywords
adaptive systems; data mining; decision support systems; neural nets; physiological models; adaptive decision support system; adaptive learning; bioinformatics; brain organization; evolving connectionist systems; genetics; knowledge discovery; neural network; Adaptive control; Adaptive systems; Bioinformatics; Biological neural networks; Brain modeling; DNA; Information processing; Natural languages; Neurons; RNA;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
Print_ISBN
981-04-7524-1
Type
conf
DOI
10.1109/ICONIP.2002.1198126
Filename
1198126
Link To Document